Dementia and neurocognitive disorders最新文献

Background and purpose: Language dysfunction is a symptom common to patients with Alzheimer's disease (AD). Speech feature analysis may be a patient-friendly screening test for early-stage AD. We aimed to investigate the speech features of amnestic mild cognitive impairment (aMCI) compared to normal controls (NCs).

Methods: Spoken responses to test questions were recorded with a microphone placed 15 cm in front of each participant. Speech samples delivered in response to four spoken test prompts (free speech test, Mini-Mental State Examination [MMSE], picture description test, and sentence repetition test) were obtained from 98 patients with aMCI and 139 NCs. Each recording was transcribed, with speech features noted. The frequency of the ten speech features assessed was evaluated to compare speech abilities between the test groups.

Results: Among the ten speech features, the frequency of pauses (p=0.001) and mumbles (p=0.001) were significantly higher in patients with aMCI than in NCs. Moreover, MMSE score was found to negatively correlate with the frequency of pauses (r=-0.441, p<0.001) and mumbles (r=-0.341, p<0.001).

Conclusions: Frequent pauses and mumbles reflect cognitive decline in aMCI patients in episodic and semantic memory tests. Speech feature analysis may prove to be a speech-based biomarker for screening early-stage cognitive impairment.

Background and purpose: There are many methods for converting scores from the Montreal Cognitive Assessment (MoCA) to those on the Mini-Mental State Examination (MMSE). In this study we aimed to validate 4 methods that convert the full score range (0-30 points) of the MoCA to an equivalent range for the MMSE.

Methods: We examined the medical records of 506 subjects who completed the MoCA and MMSE-second edition (MMSE-2) on the same day. For the validation index, we calculated mean, median, and root-mean-squared error (RMSE) of the difference between true and equivalent MMSE-2 scores. We also calculated intraclass correlation coefficients (ICCs), the Bland-Altman plot, and the generalizability coefficient between true and equivalent MMSE-2 scores for reliability. We compared the ICCs according to age, sex, education, MMSE, and cognitive-status subgroups. For accuracy, we evaluated a ±2 point difference between the true and equivalent MMSE-2 scores.

Results: The 4 conversion methods had a mean of -0.79 to -0.05, a median of -1 to 0, and an RMSE of 2.61-2.94 between true and equivalent MMSE-2 scores. All conversion methods had excellent reliability, with an ICC greater than 0.75 between true and equivalent MMSE-2 scores. These results were almost maintained in the subgroup analyses. These conversion methods provided more than 65% accuracy within ±2 points of the true MMSE-2 scores.

Conclusions: We suggest that these 4 conversion methods are applicable for converting MoCA scores to MMSE-2 scores. They will greatly enhance the usefulness of existing cognitive data in clinical and research settings.

Background and purpose: Interpreting the Rey complex figure (RCF) requires a standard RCF scoring system and clinical decision by clinicians. The interpretation of RCF using clinical decision by clinicians might not be accurate in the diagnosing of mild cognitive impairment (MCI) or dementia patients in comparison with the RCF scoring system. For this reason, a machine-learning algorithm was used to demonstrate that scoring RCF using clinical decision is not as accurate as of the RCF scoring system in predicting MCI or mild dementia patients from normal subjects.

Methods: The RCF dataset consisted of 2,232 subjects with formal neuropsychological assessments. The RCF dataset was classified into 2 datasets. The first dataset was to compare normal vs. abnormal and the second dataset was to compare normal vs. MCI vs. mild dementia. Models were trained using a convolutional neural network for machine learning. Receiver operating characteristic curves were used to compare the sensitivity, specificity, and area under the curve (AUC) of models.

Results: The trained model's accuracy for predicting cognitive states was 96% with the first dataset (normal vs. abnormal) and 88% with the second dataset (normal vs. MCI vs. mild dementia). The model had a sensitivity of 85% for detecting abnormal with an AUC of 0.847 with the first dataset. It had a sensitivity of 78% for detecting MCI or mild dementia with an AUC of 0.778 with the second dataset.

Conclusions: Based on this study, the RCF scoring system has the potential to present more accurate criteria than the clinical decision for distinguishing cognitive impairment among patients.

Background and purpose: The Korean-Color Word Stroop Test: Color Reading (K-CWST: CR) included in the Seoul Neuropsychological Screening Battery, 2nd Edition (SNSB-II) examines inhibitory control deficit. It provides normative data for both 60- and 120-second conditions, but the validity of the 60-second condition has not yet been proven. This study examined the validity of the 60-second condition by observing concordance between the performances in cognitively normal, MCI, and mild dementia groups.

Methods: There were 1,336 patients performed the SNSB-II, including the K-CWST: CR. Based on the cognitive test results, activities of daily living, and clinical interview, the patients were assigned to normal cognition (n=104), MCI (n=884), or mild dementia (n=348) groups. Abnormal performance on the K-CWST: CR was operationally defined as 1SD below the normative mean. The receiver operating characteristic curve analyses were conducted to compare the discriminability between the 60- and 120-second conditions.

Results: The percentages of abnormal performance in the MCI group were 41.5% and 42.3%, and those in the mild dementia group were 82.7% and 82.4% for the 60- and 120-second conditions, respectively. The areas under the curve for the 60- and 120-seconds were as follows; 0.80 and 0.81 in differentiating normal from MCI; 0.95 and 0.96 in normal from mild dementia; and 0.77 and 0.77 in MCI from mild dementia.

Conclusions: The 60-second condition of the K-CWST showed very similar results, not statistically different from the 120-second condition. Therefore, the 60-second condition could be used interchangeably with the 120-second condition in a clinical setting.

Background and purpose: Everyday Cognition (ECog) has been widely used to differentiate individuals with mild cognitive impairment (MCI) and dementia from normal elderly individuals. It has also been used to assess subjective cognitive decline (SCD). This study investigated the feasibility of using ECog as a screening measure for SCD in community-dwelling elderly individuals.

Methods: The participants included 84 older adults with and 93 without SCD living in the community. These 2 groups were classified based on their response ("yes" or "no") to the question "Do you perceive memory or cognitive difficulties?" All participants were evaluated using the Korean-Mini Mental State Examination (K-MMSE), Short form of the Geriatric Depression Scale (SGDS), and the Korean version of Everyday Cognition (K-ECog).

Results: The scores of all participants were within the normal range on the K-MMSE and SGDS. The total K-MMSE score did not differ significantly between the 2 groups after controlling for age, education, and depression. The scores of SCD group were significantly higher than those of the non-SCD group for memory, language, and executive function: planning domains, as well as K-ECog total score. Receiver operating characteristic curve analysis revealed that the K-ECog total score was effective in moderately differentiating between subjects with and without SCD (area under the curve: 0.73).

Conclusions: ECog is a feasible and useful screening measure for SCD in older adults living in the community, and can be used to assess the full spectrum of cognitive and functional deficits, ranging from SCD to MCI and dementia.

Background and purpose: The purpose of this study was to investigate the prevalence of mortality during hospitalization among patients diagnosed with delirium at geriatric consultations requested in the previous one year, together with the factors affecting this.

Methods: The electronic medical records of geriatric consultations requested from the psychiatry department between January 1, 2019 and December 31, 2019 were examined from the automation system. The 200 geriatric delirium patients were included in the study. Patients' age, sex, length of hospital stay (LOHS), time between hospitalization and consultation, the department requesting consultation, reason for consultation request, psychiatric recommendations after consultation, reason for hospitalization, number of comorbid medical diseases, number of daily medications used, and history of psychiatric disease were retrieved from the electronic medical records in the automation system.

Results: LOHS and time from hospitalization to consultation were longer in the exitus group. Numbers of comorbid disease and daily medications used were higher in the died patients. Male gender, higher numbers of comorbid diseases, and daily medications were predictors of death.

Conclusions: Early detection of delirium may be important for short term results of disease. When evaluating these patients, reviewing the drugs used as much as possible can affect the outcome of the disease.